Charging pile line loss estimation method, device and electronic equipment

Abstract

The present invention discloses a method, device and electronic device for estimating the line loss of a charging pile. The method comprises: obtaining the total meter electricity metering value corresponding to the target charging pile area, and the sub-meter electricity metering values ​​corresponding to the multiple charging piles in the target charging pile area; establishing a linear regression equation based on the total meter electricity metering value and the sub-meter electricity metering values ​​corresponding to the multiple charging piles; calculating the pile error estimation values ​​corresponding to the multiple charging piles and the functional relationship between the pile error estimation values ​​and the line loss estimation values ​​according to the linear regression equation; determining the target line loss incremental estimation value based on the pile error estimation values ​​corresponding to the multiple charging piles and the functional relationship; calculating the line loss estimation value according to the preset initial line loss value and the target line loss incremental estimation value. The present invention solves the technical problems of large workload of on-site calibration of charging piles and low algorithm estimation accuracy existing in the related art.

Description

Technical Field

[0001] The present invention relates to the field of error assessment, and in particular to a method, device and electronic device for estimating line loss of a charging pile. Background Art

[0002] Currently, national metrological verification regulations require that charging piles be verified every year. However, due to the large number of charging piles, their widespread distribution, and the complex operating environment, the cost of annual on-site verification of each unit is enormous. Mathematical models are used to assess the status of charging piles, allowing for targeted on-site verification based on the line loss conditions. However, the use of mathematical models to assess line loss in related technologies relies on multiple electrical parameters that are difficult to collect, resulting in additional labor and time costs, and the algorithm suffers from low accuracy.

[0003] To address the above-mentioned problems, no effective solutions have been proposed so far. Summary of the Invention

[0004] Embodiments of the present invention provide a method, device, and electronic device for estimating line loss of a charging pile, so as to at least solve the technical problems existing in the related art of heavy workload in on-site verification of charging piles and low algorithm estimation accuracy.

[0005] According to one aspect of an embodiment of the present invention, a method for estimating line loss of a charging pile is provided, comprising: obtaining a total meter electricity metering value corresponding to a target charging pile area, and sub-meter electricity metering values ​​corresponding to a plurality of charging piles in the target charging pile area; establishing a linear regression equation based on the total meter electricity metering value and the sub-meter electricity metering values ​​corresponding to the plurality of charging piles, wherein the total meter electricity metering value serves as a dependent variable in the linear regression equation, and the sub-meter electricity metering value serves as an independent variable in the linear regression equation; calculating pile error estimation values ​​corresponding to the plurality of charging piles, and a functional relationship between the pile error estimation values ​​and the line loss estimation value according to the linear regression equation; determining a target line loss incremental estimation value based on the pile error estimation values ​​corresponding to the plurality of charging piles and the functional relationship; and calculating the line loss estimation value according to a pre-set initial line loss value and the target line loss incremental estimation value.

[0006] Optionally, the target line loss incremental estimate value is determined based on the pile error estimate values ​​corresponding to the multiple charging piles and the functional relationship, including: obtaining a first pile error estimate value that meets a first preset condition among the pile error estimate values ​​corresponding to the multiple charging piles; in the case where there are multiple first pile error estimates, calculating the mean and variance corresponding to the multiple first pile error estimates; determining a second pile error estimate value according to the mean and variance; and determining the target line loss incremental estimate value based on the second pile error estimate value and the functional relationship.

[0007] Optionally, in the case where there are multiple second pile error estimates, determining the target line loss incremental estimate based on the second pile error estimates and the functional relationship includes: calculating the first line loss incremental estimate corresponding to the multiple second pile error estimates according to the functional relationship; calculating the average of the multiple first line loss incremental estimate values; and using the average as the target line loss incremental estimate.

[0008] Optionally, determining the second pile error estimate based on the mean and variance includes: obtaining a third pile error estimate among the pile error estimates corresponding to the multiple charging piles, which is greater than an estimation threshold, less than the difference between the mean and the variance, and greater than the sum of the mean and the variance; taking the pile error estimates corresponding to the multiple charging piles except the third pile error estimate as the second pile error estimate, and incorporating the second pile error estimate into the pile error set.

[0009] Optionally, before determining the target line loss incremental estimate based on the second pile error estimate and the functional relationship, the method further includes: judging whether the target line loss incremental estimate is less than a preset threshold; if the target line loss incremental estimate is less than the preset threshold, calculating the line loss estimate based on the initial line loss value and the target line loss incremental estimate.

[0010] Optionally, if the target line loss incremental estimate is greater than or equal to the preset threshold, the following operations are performed in a loop iterative manner until the updated target line loss incremental estimate is less than the preset threshold: the sum of the initial line loss value and the obtained target line loss incremental estimate is added to the linear regression equation to obtain an updated linear regression equation; the updated pile error estimates corresponding to the multiple charging piles and the updated functional relationship are calculated according to the updated linear regression equation; and the updated target line loss incremental estimate is determined based on the updated pile error estimate and the updated functional relationship.

[0011] According to another aspect of an embodiment of the present invention, a line loss estimation device for a charging pile is provided, comprising: a first acquisition module for acquiring a total meter electricity metering value corresponding to a target charging pile area, and sub-meter electricity metering values ​​corresponding to a plurality of charging piles in the target charging pile area; a first establishment module for establishing a linear regression equation based on the total meter electricity metering value and the sub-meter electricity metering values ​​corresponding to the plurality of charging piles, wherein the total meter electricity metering value serves as a dependent variable in the linear regression equation, and the sub-meter electricity metering value serves as an independent variable in the linear regression equation; a first calculation module for calculating, according to the linear regression equation, pile error estimation values ​​corresponding to the plurality of charging piles, and a functional relationship between the pile error estimation values ​​and the line loss estimation value; a first determination module for determining a target line loss incremental estimation value based on the pile error estimation values ​​corresponding to the plurality of charging piles and the functional relationship; and a second calculation module for calculating the line loss estimation value based on a preset initial line loss value and the target line loss incremental estimation value.

[0012] Optionally, the first determination module includes: a second acquisition unit, used to obtain the first pile error estimation value that meets the first preset condition among the pile error estimation values ​​corresponding to the multiple charging piles; a third calculation unit, used to calculate the mean and variance corresponding to the multiple first pile error estimation values ​​when there are multiple first pile error estimation values; a second determination unit, used to determine the second pile error estimation value based on the mean and variance; and a third determination unit, used to determine the target line loss incremental estimation value based on the second pile error estimation value and the functional relationship.

[0013] According to another aspect of an embodiment of the present invention, a non-volatile storage medium is provided, wherein the non-volatile storage medium stores a plurality of instructions, wherein the instructions are suitable for being loaded by a processor and executed by any one of the charging pile line loss estimation methods.

[0014] According to another aspect of an embodiment of the present invention, an electronic device is provided, comprising: one or more processors and a memory, the memory being used to store one or more programs, wherein when the one or more programs are executed by the one or more processors, the one or more processors implement any one of the charging pile line loss estimation methods.

[0015] In an embodiment of the present invention, a mathematical model is established by obtaining the total meter electricity metering value corresponding to the target charging pile area and the sub-meter electricity metering values ​​corresponding to the multiple charging piles in the target charging pile area; a linear regression equation is established based on the total meter electricity metering value and the sub-meter electricity metering values ​​corresponding to the multiple charging piles, wherein the total meter electricity metering value serves as the dependent variable in the linear regression equation, and the sub-meter electricity metering value serves as the independent variable in the linear regression equation; according to the linear regression equation, pile error estimation values ​​corresponding to the multiple charging piles and the functional relationship between the pile error estimation value and the line loss estimation value are calculated; based on the pile error estimation values ​​corresponding to the multiple charging piles and the functional relationship, a target line loss incremental estimation value is determined; and the line loss estimation value is calculated according to a pre-set initial line loss value and the target line loss incremental estimation value. The purpose of performing calculations based on existing metering values ​​and obtaining high-precision line loss estimates for real-time on-site calibration of charging piles is achieved, and the technical effect of improving the accuracy of line loss estimation and reducing the workload of on-site calibration of charging piles is realized, thereby solving the technical problems of large on-site calibration workload of charging piles and low algorithm estimation accuracy existing in related technologies. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] The drawings described herein are used to provide a further understanding of the present invention and constitute a part of this application. The exemplary embodiments of the present invention and their descriptions are used to explain the present invention and do not constitute an improper limitation of the present invention. In the drawings:

[0017] Figure 1 is a flow chart of a method for estimating line loss of a charging pile provided in an embodiment of the present invention;

[0018] Figure 2 is a linear regression relationship diagram provided according to an embodiment of the present invention;

[0019] Figure 3 2 is a schematic diagram of a line loss estimation device for a charging pile provided according to an embodiment of the present invention. DETAILED DESCRIPTION

[0020] In order to enable those skilled in the art to better understand the solutions of the present invention, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the embodiments described are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts should fall within the scope of protection of the present invention.

[0021] It should be noted that the terms "first", "second", etc. in the description and claims of the present invention and the above-mentioned drawings are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that the numbers used in this way can be interchanged where appropriate, so that the embodiments of the present invention described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions. For example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0022] According to an embodiment of the present invention, a method embodiment of a method for estimating line losses of a charging pile is provided. It should be noted that the steps shown in the flowchart of the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions, and although a logical order is shown in the flowchart, in some cases, the steps shown or described can be executed in an order different from that shown here.

[0023] Figure 1 is a method for estimating the line loss of a charging pile according to an embodiment of the present invention, such as Figure 1 As shown, the method includes the following steps:

[0024] Step S102, obtaining a total meter power measurement value corresponding to a target charging pile area, and sub-meter power measurement values ​​corresponding to a plurality of charging piles in the target charging pile area;

[0025] Step S104: establishing a linear regression equation based on the total meter power measurement value and the sub-meter power measurement values ​​corresponding to the plurality of charging piles, wherein the total meter power measurement value serves as the dependent variable in the linear regression equation, and the sub-meter power measurement values ​​serve as the independent variable in the linear regression equation;

[0026] Step S106, calculating according to the linear regression equation the pile error estimation values ​​corresponding to the plurality of charging piles, and the functional relationship between the pile error estimation values ​​and the line loss estimation value;

[0027] Step S108, determining a target line loss increment estimate based on the pile error estimates corresponding to the plurality of charging piles and the functional relationship;

[0028] Step S110 , calculating the line loss estimate value based on a preset initial line loss value and the target line loss incremental estimate value.

[0029] Through the above steps, it is possible to achieve the purpose of performing calculations based on existing measurement values ​​and obtaining high-precision line loss estimates for real-time on-site calibration of charging piles, thereby achieving the technical effect of improving the accuracy of line loss estimation and reducing the workload of on-site calibration of charging piles, thereby solving the technical problems existing in related technologies of large on-site calibration workload of charging piles and low algorithm estimation accuracy.

[0030] In the charging pile line loss estimation method provided in an embodiment of the present invention, the total meter power measurement corresponding to the target charging pile area and the sub-meter power measurement values ​​corresponding to the multiple charging piles are data already obtained by the operator during normal use, eliminating the need for additional data collection. Based on these total meter power measurement values ​​and the sub-meter power measurement values ​​corresponding to the multiple charging piles, a linear regression equation is established, with the total meter power measurement value serving as the dependent variable and the sub-meter power measurement values ​​serving as the independent variable. Linear regression is performed to obtain pile error estimates corresponding to the multiple charging piles, and a functional relationship between the pile error estimates and the line loss estimates is determined. Based on the pile error estimates and this functional relationship, a target line loss incremental estimate is determined. The line loss estimate is calculated based on a preset initial line loss value and the target line loss incremental estimate. The obtained line loss estimates for the multiple charging piles can characterize their status, facilitating technical personnel's determination of which charging piles require on-site calibration. The obtained line loss estimates provide guidance for on-site calibration, facilitating the rational allocation of human resources and reducing workload.

[0031] Optionally, the algorithm of the above-mentioned charging pile line loss estimation method can have multiple application scopes, for example: the algorithm application scope is: (1) the number of out-of-tolerance piles in the charging piles does not exceed 1 / 3 of the total number of piles; (2) the mean value of the pile error of the non-out-of-tolerance piles does not exceed 1; (3) the absolute value of the pile error of the out-of-tolerance piles is not less than 2; (4) the number of charging piles in the target charging pile area is not less than 30.

[0032] Optionally, for a single charging pile, the actual consumption value is represented by the sub-meter power measurement value. The relationship between the actual consumption value and the sub-meter power measurement value can be various. For example, there are m charging piles, j represents the sequence number of the charging pile, and i represents the cycle sequence number. The actual value of the power consumption of the j-th charging pile in the time period corresponding to the i-th cycle is expressed as φ j (i), the measurement value of the power consumption of the j-th charging pile in the time period corresponding to the i-th cycle is expressed as x j (i), the regression coefficient of the jth charging pile is expressed as a j , the relationship between the true value and the measured value is expressed as x j (i) = a j φ j (i). Among them, aj It is expressed as an estimated value obtained using the linear regression method, which is a known quantity in the relationship between the true value and the measured value. Each charging station corresponds to a regression coefficient.

[0033] Optionally, the above linear regression equation can be multiple, for example, established as Where y(i) represents the total metered electricity value corresponding to the target charging pile area, e0 represents the total average fixed electricity loss, and ε(i) represents the random error value. Due to the presence of multiple charging piles, the corresponding matrix form is Y = Xa + ε, where Y represents the column vector corresponding to the total metered electricity value corresponding to the target charging pile area, X represents the matrix with i rows and j columns corresponding to the sub-metered electricity value, a represents the column vector corresponding to the regression coefficient, and ε represents the column vector corresponding to the random error value.

[0034] Optionally, the functional relationship between the pile error estimate and the line loss estimate can be various. For example, under the ideal condition that the pile error is considered to be 0, the expression is: in, Expressed as an estimate of the pile error, Expressed as an estimated line loss value.

[0035] Optionally, the above-mentioned preset initial line loss value is a positive value less than 1, and multiple values ​​can be taken within the above-mentioned range. For example, based on historical data, reasonable values ​​are taken within the above-mentioned range, and the above-mentioned preset initial line loss value is selected as 0.2, and so on.

[0036] In an optional embodiment, the target line loss incremental estimate value is determined based on the pile error estimate values ​​corresponding to the above-mentioned multiple charging piles and the above-mentioned functional relationship, including: obtaining a first pile error estimate value that meets a first preset condition among the pile error estimate values ​​corresponding to the above-mentioned multiple charging piles; in the case that there are multiple first pile error estimates, calculating the mean and variance corresponding to the multiple first pile error estimates; determining a second pile error estimate value based on the above-mentioned mean and variance; and determining the target line loss incremental estimate value based on the above-mentioned second pile error estimate value and the above-mentioned functional relationship.

[0037] It can be understood that, from the pile error estimates corresponding to the multiple charging piles, multiple first pile error estimates that meet the first preset condition are obtained. Based on these multiple first pile error estimates, the corresponding mean and variance are calculated. A second pile error estimate is determined based on the mean and variance. The target line loss increment estimate is determined based on the functional relationship between the second pile error estimate, the pile error estimates, and the line loss estimate.

[0038] Optionally, there may be multiple ways to obtain the first preset condition. For example, the first preset condition is that the corresponding pile error estimation value is less than 0, and so on.

[0039] In an optional embodiment, in the case where there are multiple second pile error estimates, the target line loss incremental estimate is determined based on the second pile error estimates and the functional relationship, including: calculating the first line loss incremental estimate corresponding to the multiple second pile error estimates according to the functional relationship; calculating the average of the multiple first line loss incremental estimates; and using the average as the target line loss incremental estimate.

[0040] It can be understood that the first line loss incremental estimate is obtained based on the second pile error estimate and the above functional relationship. The average value of the multiple first line loss incremental estimates is calculated, and the obtained average value is used as the target line loss incremental estimate.

[0041] Optionally, the above-mentioned multiple first line loss incremental estimated values ​​are averaged, and the calculation result obtained by the above-mentioned average calculation reflects that the multiple first line loss incremental estimated values ​​are statistically processed and characterized. There are many ways to obtain the average value, for example, the arithmetic mean, geometric mean, harmonic mean, weighted mean, square mean, etc.

[0042] In an optional embodiment, the second pile error estimate value is determined based on the above-mentioned mean and variance, including: obtaining a third pile error estimate value among the pile error estimate values ​​corresponding to the above-mentioned multiple charging piles, which is greater than the estimation threshold, less than the difference between the above-mentioned mean and the above-mentioned variance, and greater than the sum of the above-mentioned mean and the above-mentioned variance; using the pile error estimate values ​​corresponding to the above-mentioned multiple charging piles except the above-mentioned third pile error estimate value as the above-mentioned second pile error estimate value, and incorporating the above-mentioned second pile error estimate value into the pile error set.

[0043] It can be understood that the selection conditions are that the corresponding pile error estimate is greater than the estimation threshold, less than the difference between the above-mentioned mean and the above-mentioned variance, and greater than the sum of the above-mentioned mean and the above-mentioned variance. The pile error corresponding to the plurality of charging piles that meets these conditions is obtained as the third pile error estimate. The third pile error estimate is removed, and the remaining pile error estimate corresponding to the plurality of charging piles is used as the second pile error estimate. The second pile error estimate is included in the pile error set.

[0044] Optionally, the above-mentioned estimation threshold may be multiple, for example, the estimation threshold is 0, and so on.

[0045] Optionally, the above-mentioned pile error set can be of multiple types. For example, the error set includes the above-mentioned second pile error estimation value and the charging pile serial number corresponding to the second pile error estimation value.

[0046] Optionally, the serial number of the charging pile corresponding to the third pile error estimate is obtained. In the above method, the charging piles corresponding to the pile error estimate values ​​greater than the estimation threshold, less than the difference between the mean and the variance, and greater than the sum of the mean and the variance are considered to have large actual deviations. The serial numbers of these charging piles are then obtained to guide on-site verification.

[0047] In an optional embodiment, before determining the target line loss incremental estimate based on the second pile error estimate and the functional relationship, the method further includes: judging whether the target line loss incremental estimate is less than a preset threshold; if the target line loss incremental estimate is less than the preset threshold, calculating the line loss estimate based on the initial line loss value and the target line loss incremental estimate.

[0048] It can be understood that the relationship between the target line loss incremental estimate and a preset threshold is determined. If the determination result is that the target line loss incremental estimate is less than the preset threshold, the target line loss incremental estimate is obtained. The line loss estimate is then calculated based on the initial line loss value and the target line loss incremental estimate.

[0049] Optionally, the above-mentioned iterative method uses the condition that the updated target line loss incremental estimate is less than the above-mentioned preset threshold as the condition for terminating the iteration. In actual applications, the termination condition may be various. For example, if the above-mentioned termination condition cannot be met after multiple iterations, a preset number of iterations may be required. The number of iterations performed is obtained as the first number of iterations, and it is determined whether the first number of iterations reaches the preset number of iterations. If the determination result is that the number of iterations reaches the preset number of iterations, the iteration is terminated, the iteration result is output, and a prompt message is issued.

[0050] In an optional embodiment, the above method also includes: if the above target line loss incremental estimate is greater than or equal to the above preset threshold, the following operations are performed in a loop iterative manner until the above updated target line loss incremental estimate is less than the above preset threshold: the sum of the above initial line loss value and the above target line loss incremental estimate that has been obtained is added to the above linear regression equation to obtain an updated linear regression equation; according to the above updated linear regression equation, the updated pile error estimates corresponding to the above multiple charging piles and the updated functional relationship are calculated; based on the above updated pile error estimates and the above updated functional relationship, the updated target line loss incremental estimate is determined.

[0051] It can be understood that when the target line loss incremental estimate is greater than or equal to the preset threshold, it is processed in a loop iterative manner, and the linear regression equation is updated based on the sum of the initial line loss value and the target line loss incremental estimate that has been obtained. According to the updated linear regression equation, the updated pile error estimate and the updated functional relationship are obtained. Based on the obtained updated pile error estimate and the updated functional relationship, the updated target line loss incremental estimate is obtained. Continue to judge the size relationship with the preset threshold, and repeat the above process until the updated target line loss incremental estimate is less than the preset threshold, which is deemed to meet the iteration end condition and end the loop.

[0052] Based on the above embodiments and optional embodiments, the present invention proposes an optional implementation manner.

[0053] The theoretical basis of the present invention is: assuming that the total meter electricity consumption value corresponding to the target charging pile area is accurate, according to the law of conservation of energy, the total meter electricity consumption value corresponding to the target charging pile area is only composed of the true value of the electricity consumption corresponding to multiple charging piles, line loss and the total average fixed electricity loss. Figure 2 This is a linear regression relationship diagram provided by an embodiment of the present invention. For a single charging pile, the sub-meter electricity measurement value is used to represent the actual consumption value. The relationship diagram is obtained from the sum of the sub-meter electricity measurement values ​​corresponding to multiple charging piles and the total meter electricity measurement value corresponding to the target charging pile area ( Figure 2 ) It can be seen that the two show an obvious linear relationship, which provides good conditions for the use of linear regression models.

[0054] A single charging pile uses the sub-meter electricity measurement value to represent the actual consumption value. The relationship between the actual consumption value and the sub-meter electricity measurement value is expressed as x j (i) = a j φ j (i), derived to obtain Where j represents the serial number of the charging pile, and i represents the cycle number. j (i) is expressed as the actual value of the power consumption of the j-th charging pile in the time period corresponding to the i-th cycle, x j (i) is expressed as the measured value of the power consumption of the j-th charging pile in the time period corresponding to the i-th cycle, a j Expressed as the regression coefficient of the j-th charging pile, ω j It is expressed as the pile error corresponding to the jth charging pile. j It is expressed as an estimated value obtained by linear regression method. In the relationship between the true value and the measured value, it is a known quantity. Each charging pile corresponds to a regression coefficient, so based on the relationship between the true value and the measured value Get ω j value.

[0055] Based on the above theoretical basis and known quantities, the specific steps of the optional implementation method are as follows:

[0056] Step S1: obtaining a total meter power measurement value corresponding to a target charging pile area, and sub-meter power measurement values ​​corresponding to a plurality of charging piles in the target charging pile area.

[0057] It can be understood that when the line loss is unknown, direct linear regression without considering the line loss usually has obvious negative deviations. The reason for these negative deviations is that the line loss is not taken into account. Usually the line loss is unknown. In order to estimate the line loss, some electrical parameters are needed, such as power supply radius, low-voltage circuit length, load rate, power consumption ratio, maximum power supply length, and distribution transformer load rate. These parameters are difficult to obtain directly, which increases the collection cost, labor cost and time cost. The total meter electricity measurement value corresponding to the target charging pile area and the sub-meter electricity measurement value corresponding to multiple charging piles are data obtained by the operator during normal use, and no additional collection is required. The total meter electricity measurement value corresponding to the target charging pile area in the time period corresponding to the i-th cycle is expressed as y(i). The sub-meter electricity measurement value corresponding to multiple charging piles is expressed as φ j (i) Both of the above quantities are known quantities that can be obtained.

[0058] Step S2: establishing a linear regression equation based on the total meter power measurement value and the sub-meter power measurement values ​​corresponding to the plurality of charging piles.

[0059] Optionally, the total meter electricity measurement value is used as the dependent variable in the linear regression equation, and the sub-meter electricity measurement value is used as the independent variable in the linear regression equation. Among them, e0 is expressed as the total average fixed power loss, and ε(i) is expressed as the random error value.

[0060] In step S21, since there are multiple charging piles, the corresponding conversion is performed into a matrix form and expressed as Y = Xa + ε, where Y is expressed as the column vector corresponding to the total meter power measurement value corresponding to the target charging pile area, X is expressed as the matrix with i rows and j columns corresponding to the sub-meter power measurement value, a is expressed as the column vector corresponding to the regression coefficient, and ε is expressed as the column vector corresponding to the random error value.

[0061] Step S22, calculate the least squares solution to be When considering line loss, let the initial line loss value be λ, and the expression is Y=Y0(1+λ%), where Y0 is the sum of the actual value of power consumption and the actual value of fixed loss. The expression is further obtained as Among them, a0 is the true coefficient, which is expressed as a0=(X T X)-1 X T Y0.

[0062] Step S3, calculating according to the linear regression equation the pile error estimation values ​​corresponding to the plurality of charging piles, and the functional relationship between the pile error estimation values ​​and the line loss estimation value.

[0063] Step S31, based on the relationship between the true value and the measured value Get ω j value.

[0064] Step S32: Obtain the pile error expression considering line loss: in, is the estimated value of the pile error. Based on the derivation results of the above steps S22 and S31, the expression is obtained as

[0065] Step S33, set the actual error of the charging pile to ω0, and obtain the expression: Based on the ideal condition that ω0 is approximately 0, the expression is obtained The functional relationship between the pile error estimate and the line loss estimate is further obtained as follows: in, Expressed as an estimated line loss value.

[0066] Step S4: determining a target line loss increment estimate based on the pile error estimates corresponding to the plurality of charging piles and the functional relationship.

[0067] In step S41, a preset initial line loss value is 0.2, and a first pile error estimation value that meets a first preset condition is obtained from the pile error estimation values ​​corresponding to the above-mentioned multiple charging piles, wherein the first preset condition is that the corresponding pile error estimation value is less than 0.

[0068] Step S42: When there are multiple first pile error estimation values, calculate the mean e and variance s corresponding to the multiple first pile error estimation values.

[0069] Step S43: Determine a second pile error estimate based on the mean and variance. Obtain a third pile error estimate from the pile error estimates corresponding to the plurality of charging piles that is greater than 0, less than the difference between the mean e and the variance e, and greater than the sum of the mean e and the variance s. The pile error estimates corresponding to the plurality of charging piles, excluding the third pile error estimate, are used as the second pile error estimate, and the second pile error estimate is included in the pile error set Ω.

[0070] Step S44: determining and obtaining the target line loss increment estimate based on the second pile error estimate and the functional relationship.

[0071] Optionally, the above functional relationship can be expressed as Based on the functional relationship, first incremental line loss estimates corresponding to multiple second pile error estimates are calculated; the average of the multiple first incremental line loss estimates is calculated as a target incremental line loss estimate. A determination is made as to whether the target incremental line loss estimate is less than a preset threshold. If the target incremental line loss estimate is greater than or equal to the preset threshold, an iterative loop is implemented, where the sum of the initial line loss value and the previously obtained target incremental line loss estimate is added to the linear regression equation to obtain an updated linear regression equation. Based on the updated linear regression equation, updated pile error estimates corresponding to the multiple charging piles and an updated functional relationship are calculated. An updated target incremental line loss estimate is determined based on the updated pile error estimates and the updated functional relationship until the updated target incremental line loss estimate is less than the preset threshold, thereby obtaining the target incremental line loss. If the termination condition is not met after multiple loops, a preset number of loop iterations is required. The number of loop iterations performed is obtained as the first loop iteration number, and a determination is made as to whether the first loop iteration number reaches the preset number of loop iterations. If so, the loop iteration ends, the loop iteration result is output, and a prompt message is issued. If the estimated value of the target line loss increment is less than the preset threshold, step S5 is performed based on the target line loss increment.

[0072] In step S5, the preset initial line loss value and the target line loss incremental estimated value are summed to obtain the line loss estimated value. The charging pile status represented by the line loss estimated value can guide relevant personnel to carry out on-site calibration work in a targeted manner.

[0073] It should be noted that the national metrological verification regulations require that the calibration cycle of charging piles should not exceed one year, and on-site metrological verification of charging piles should be carried out annually for each charging pile. However, due to the large number of charging piles, their wide distribution, and the complex operating environment, the cost of on-site calibration of each charging pile is huge. At the same time, there are problems such as "blind calibration, insufficient calibration, frequent calibration, and excessive calibration." The above-mentioned optional implementation method can obtain real-time operating data from the operating manufacturer, establish a mathematical model, analyze the status of the charging pile (represented by the estimated value of line loss), and guide the inspection personnel to conduct on-site calibration. It greatly reduces the workload of on-site calibration and makes the calibration work more targeted.

[0074] It should still be noted that the steps shown in the flowcharts of the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions, and that, although a logical order is shown in the flowcharts, in some cases, the steps shown or described can be executed in an order different from that shown here.

[0075] In this embodiment, a line loss estimation device for a charging pile is also provided, which is used to implement the above-mentioned embodiments and preferred implementation modes, and the details that have been explained will not be repeated here. As used below, the terms "module" and "device" can be a combination of software and / or hardware that implements a predetermined function. Although the devices described in the following embodiments are preferably implemented in software, implementation in hardware, or a combination of software and hardware, is also possible and conceivable.

[0076] According to an embodiment of the present invention, there is also provided an embodiment of a device for implementing a method for estimating line loss of a charging pile. Figure 3 is a schematic diagram of a line loss estimation device for a charging pile according to an embodiment of the present invention. Figure 3 As shown, the above-mentioned charging pile line loss estimation device includes a first acquisition module 202, a first establishment module 204, a first calculation module 206, a first determination module 208, and a second calculation module 210. The device is described below.

[0077] The first acquisition module 202 is used to obtain the total meter power measurement value corresponding to the target charging pile area, and the sub-meter power measurement values ​​corresponding to the multiple charging piles in the target charging pile area;

[0078] A first establishing module 204, connected to the first acquiring module 202, is configured to establish a linear regression equation based on the total meter power measurement value and the sub-meter power measurement values ​​corresponding to the plurality of charging piles, wherein the total meter power measurement value serves as a dependent variable in the linear regression equation, and the sub-meter power measurement values ​​serve as independent variables in the linear regression equation;

[0079] A first calculation module 206 is connected to the first establishment module 204 and is used to calculate the pile error estimation values ​​corresponding to the plurality of charging piles, and the functional relationship between the pile error estimation values ​​and the line loss estimation value according to the linear regression equation;

[0080] A first determining module 208 is connected to the first calculating module 206 and is configured to determine a target line loss increment estimate based on the pile error estimates corresponding to the plurality of charging piles and the functional relationship;

[0081] The second calculation module 210 is connected to the first determination module 208 and is configured to calculate the line loss estimate value according to a preset initial line loss value and the target line loss incremental estimate value.

[0082] In a line loss estimation device for a charging pile provided by an embodiment of the present invention, a first acquisition module is set to obtain the total meter electricity measurement value corresponding to the target charging pile area, and the sub-meter electricity measurement values ​​corresponding to multiple charging piles in the above-mentioned target charging pile area; a first establishment module is used to establish a linear regression equation based on the above-mentioned total meter electricity measurement value and the sub-meter electricity measurement values ​​corresponding to the above-mentioned multiple charging piles, wherein the above-mentioned total meter electricity measurement value serves as the dependent variable in the above-mentioned linear regression equation, and the above-mentioned sub-meter electricity measurement value serves as the independent variable in the above-mentioned linear regression equation; a first calculation module is used to calculate the pile error estimation values ​​corresponding to the above-mentioned multiple charging piles, and the functional relationship between the above-mentioned pile error estimation values ​​and the line loss estimation values ​​according to the above-mentioned linear regression equation; a first determination module is used to determine the target line loss incremental estimation value based on the pile error estimation values ​​corresponding to the above-mentioned multiple charging piles and the above-mentioned functional relationship; a second calculation module is used to calculate the above-mentioned line loss estimation value according to a pre-set initial line loss value and the above-mentioned target line loss incremental estimation value. The purpose of performing calculations based on existing metering values ​​and obtaining high-precision line loss estimates for real-time on-site calibration of charging piles is achieved, and the technical effect of improving the accuracy of line loss estimation and reducing the workload of on-site calibration of charging piles is realized, thereby solving the technical problems of large on-site calibration workload of charging piles and low algorithm estimation accuracy existing in related technologies.

[0083] As an optional embodiment, in the charging pile line loss estimation device provided by an embodiment of the present invention, the first determination module includes:

[0084] The second acquiring unit 212 is configured to acquire a first pile error estimation value that satisfies a first preset condition among the pile error estimation values ​​corresponding to the plurality of charging piles;

[0085] The third calculating unit 214 is connected to the second obtaining unit 212 and is used to calculate the mean and variance corresponding to the plurality of the first pile error estimation values ​​when there are a plurality of the first pile error estimation values;

[0086] A second determining unit 216, connected to the third calculating unit 214, is configured to determine a second pile error estimate value based on the mean and variance;

[0087] The third determining unit 218 is connected to the second determining unit 216 and is configured to determine the target line loss increment estimate based on the second pile error estimate and the functional relationship.

[0088] It should be noted that the above modules can be implemented by software or hardware. For example, for the latter, it can be implemented in the following ways: the above modules can be located in the same processor; or the above modules can be located in different processors in any combination.

[0089] It should be noted that the first acquisition module 202, first establishment module 204, first calculation module 206, first determination module 208, and second calculation module 210 described above correspond to steps S102 to S110 in the embodiment. The examples and application scenarios implemented by these modules and corresponding steps are the same, but are not limited to the contents disclosed in the above embodiment. It should be noted that the above modules, as part of the device, can be run on a computer terminal.

[0090] It should be noted that the optional or preferred implementation of this embodiment can be found in the relevant description in the embodiment, which will not be repeated here.

[0091] The above-mentioned virtual learning scenario construction device based on the power system can also include a processor and a memory. The first acquisition module 202, the first establishment module 204, the first calculation module 206, the first determination module 208, the second calculation module 210, etc. are all stored in the memory as program units, and the processor executes the above-mentioned program units stored in the memory to realize the corresponding functions.

[0092] The processor includes a kernel, which retrieves the corresponding program unit from memory. There can be one or more kernels. Memory may include non-permanent memory in a computer-readable medium, random access memory (RAM), and / or non-volatile memory, such as read-only memory (ROM) or flash RAM. Memory includes at least one memory chip.

[0093] An embodiment of the present invention provides a non-volatile storage medium having a program stored thereon. When the program is executed by a processor, a method for estimating line loss of a charging pile is implemented.

[0094] An embodiment of the present invention provides an electronic device, which includes a processor, a memory, and a program stored in the memory and executable on the processor. When the processor executes the program, the following steps are implemented: obtaining a total meter electricity meter value corresponding to a target charging pile area, and sub-meter electricity meter values ​​corresponding to a plurality of charging piles in the target charging pile area; establishing a linear regression equation based on the total meter electricity meter value and the sub-meter electricity meter values ​​corresponding to the plurality of charging piles, wherein the total meter electricity meter value serves as the dependent variable in the linear regression equation, and the sub-meter electricity meter values ​​serve as the independent variable in the linear regression equation; calculating pile error estimates corresponding to the plurality of charging piles, and a functional relationship between the pile error estimates and the line loss estimates, according to the linear regression equation; determining a target line loss incremental estimate based on the pile error estimates corresponding to the plurality of charging piles and the functional relationship; and calculating the line loss estimate based on a pre-set initial line loss value and the target line loss incremental estimate. The device herein may be a server, a PC, or the like.

[0095] The present invention also provides a computer program product, which, when executed on a data processing device, is suitable for executing an initialized program having the following method steps: obtaining a total meter electricity measurement value corresponding to a target charging pile area, and sub-meter electricity measurement values ​​corresponding to a plurality of charging piles in the target charging pile area; establishing a linear regression equation based on the total meter electricity measurement value and the sub-meter electricity measurement values ​​corresponding to the plurality of charging piles, wherein the total meter electricity measurement value serves as a dependent variable in the linear regression equation, and the sub-meter electricity measurement value serves as an independent variable in the linear regression equation; calculating according to the linear regression equation pile error estimation values ​​corresponding to the plurality of charging piles, and a functional relationship between the pile error estimation values ​​and the line loss estimation value; determining a target line loss incremental estimation value based on the pile error estimation values ​​corresponding to the plurality of charging piles and the functional relationship; and calculating according to a pre-set initial line loss value and the target line loss incremental estimation value to obtain the line loss estimation value.

[0096] It will be understood by those skilled in the art that embodiments of the present invention may be provided as methods, systems, or computer program products. Thus, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware. Furthermore, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to magnetic disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0097] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowcharts and / or block diagrams, as well as combinations of processes and / or blocks in the flowcharts and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowcharts and / or block diagrams. Figure 1 a process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0098] These computer program instructions may also be stored in a computer readable memory that can direct a computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 a process or multiple processes and / or boxes Figure 1 The function specified in one or more boxes.

[0099] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operational steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing the instructions executed on the computer or other programmable device for implementing the process. Figure 1 a process or multiple processes and / or boxes Figure 1 A step that specifies a function in one or more boxes.

[0100] In a typical configuration, a computing device includes one or more processors (CPUs), input / output interfaces, network interfaces, and memory.

[0101] The memory may include non-permanent memory in a computer-readable medium, random access memory (RAM) and / or non-volatile memory in the form of read-only memory (ROM) or flash RAM. The memory is an example of a computer-readable medium.

[0102] Computer-readable media includes permanent and non-permanent, removable and non-removable media that can be implemented by any method or technology to store information. The information can be computer-readable instructions, data structures, program modules or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technology, compact disc read-only memory (CD-ROM), digital versatile disc (DVD) or other optical storage, magnetic cassettes, magnetic disk storage or other magnetic storage devices or any other non-transmission media that can be used to store information that can be accessed by a computing device. As defined herein, computer-readable media does not include transitory computer-readable media (transitory media), such as modulated data signals and carrier waves.

[0103] It should also be noted that the terms "comprises," "includes," or any other variations thereof are intended to encompass non-exclusive inclusion, such that a process, method, commodity, or apparatus that includes a list of elements includes not only those elements but also other elements not explicitly listed, or elements inherent to such process, method, commodity, or apparatus. In the absence of further limitations, an element defined by the phrase "comprises a..." does not preclude the presence of additional identical elements in the process, method, commodity, or apparatus that includes the element.

[0104] Those skilled in the art will appreciate that embodiments of the present invention may be provided as methods, systems, or computer program products. Thus, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to magnetic disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0105] The above are merely embodiments of the present invention and are not intended to limit the present invention. It will be apparent to those skilled in the art that various modifications and variations of the present invention are possible. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention are intended to be included within the scope of the claims of the present invention.

Claims

1. A method for estimating line loss of a charging pile, characterized in that: include: Obtaining a total meter power measurement value corresponding to a target charging pile area, and sub-meter power measurement values ​​corresponding to a plurality of charging piles in the target charging pile area; Based on the total meter electricity measurement value and the sub-meter electricity measurement values ​​corresponding to the multiple charging piles, a linear regression equation is established, wherein the total meter electricity measurement value is used as the dependent variable in the linear regression equation, and the sub-meter electricity measurement value is used as the independent variable in the linear regression equation; Calculating the pile error estimation values ​​corresponding to the plurality of charging piles respectively and the functional relationship between the pile error estimation values ​​and the line loss estimation values ​​according to the linear regression equation; Determine a target line loss increment estimate based on the pile error estimate values ​​corresponding to the plurality of charging piles and the functional relationship; The line loss estimate is calculated based on a preset initial line loss value and the target line loss incremental estimate value; The linear regression equation is established in the following way: Among them, y(i) is the total meter electricity measurement value, a j is the estimated value obtained by linear regression method, φ j (i) is the actual value of the power consumption of the jth charging pile among the multiple charging piles in the time period corresponding to the i-th cycle, and a j φ j (i) = x j (i), x j (i) is the sub-meter power consumption value of the j-th charging pile in the time period corresponding to the i-th cycle, e0 is the total average fixed power loss, ε(i) is the random error value, and m is the total number of the multiple charging piles; Under the ideal condition that the pile error is regarded as 0, the pile error estimation values ​​corresponding to the plurality of charging piles, and the functional relationship between the pile error estimation value and the line loss estimation value are established in the following manner: in, is the estimated value of the pile error, is the estimated value of the line loss.

2. The method according to claim 1, characterized in that The step of determining a target line loss increment estimate value based on the pile error estimate values ​​respectively corresponding to the plurality of charging piles and the functional relationship comprises: Obtaining a first pile error estimation value that satisfies a first preset condition among the pile error estimation values ​​corresponding to the plurality of charging piles; In the case where there are multiple first pile error estimation values, calculating means and variances corresponding to the multiple first pile error estimation values; Determine a second pile error estimate value according to the mean and variance; The target line loss increment estimate is determined based on the second pile error estimate and the functional relationship.

3. The method according to claim 2, characterized in that In the case where there are multiple second pile error estimation values, determining the target line loss increment estimation value based on the second pile error estimation value and the functional relationship includes: Calculate and obtain first line loss increment estimated values ​​corresponding to a plurality of second pile error estimated values ​​respectively according to the functional relationship; Calculating an average of a plurality of first line loss increment estimation values; The average value is used as the target line loss increment estimation value.

4. The method according to claim 2, characterized in that: Determining a second pile error estimate value according to the mean and the variance includes: Obtain a third pile error estimation value, which is greater than an estimation threshold, less than a difference between the mean and the variance, and greater than a sum of the mean and the variance, among the pile error estimation values ​​corresponding to the plurality of charging piles respectively; The pile error estimation values ​​corresponding to the plurality of charging piles except the third pile error estimation value are used as the second pile error estimation value, and the second pile error estimation value is included in the pile error set.

5. The method according to claim 2, characterized in that: Before determining the target line loss increment estimate based on the second pile error estimate and the functional relationship, the method further includes: Determining whether the target line loss increment estimate is less than a preset threshold; If the target line loss incremental estimated value is less than the preset threshold, the line loss estimated value is calculated based on the initial line loss value and the target line loss incremental estimated value.

6. The method according to claim 5, characterized in that The method further comprises: If the target line loss incremental estimate is greater than or equal to the preset threshold, the following operations are performed in a loop iterative manner until the updated target line loss incremental estimate is less than the preset threshold: the sum of the initial line loss value and the target line loss incremental estimate that has been obtained is added to the linear regression equation to obtain an updated linear regression equation; the updated pile error estimates corresponding to the multiple charging piles are calculated according to the updated linear regression equation, as well as the updated functional relationship; the updated target line loss incremental estimate is determined based on the updated pile error estimates and the updated functional relationship.

7. A charging pile line loss estimation device, characterized in that: include: A first acquisition module is used to obtain a total meter power measurement value corresponding to a target charging pile area, and sub-meter power measurement values ​​corresponding to a plurality of charging piles in the target charging pile area; A first establishing module, configured to establish a linear regression equation based on the total meter electricity measurement value and the sub-meter electricity measurement values ​​corresponding to the plurality of charging piles, wherein the total meter electricity measurement value serves as a dependent variable in the linear regression equation, and the sub-meter electricity measurement value serves as an independent variable in the linear regression equation; A first calculation module, configured to calculate, according to the linear regression equation, pile error estimation values ​​corresponding to the plurality of charging piles, and a functional relationship between the pile error estimation values ​​and the line loss estimation values; A first determination module, configured to determine a target line loss increment estimation value based on the pile error estimation values ​​corresponding to the plurality of charging piles and the functional relationship; A second calculation module, configured to calculate the line loss estimate value according to a preset initial line loss value and the target line loss incremental estimate value; The first establishing module is further used to establish the linear regression equation in the following manner: Among them, y(i) is the total meter electricity measurement value, a j is the estimated value obtained by linear regression method, φ j (i) is the actual value of the power consumption of the jth charging pile among the multiple charging piles in the time period corresponding to the i-th cycle, and a j φ j (i) = x j (i), x j (i) is the sub-meter power consumption value of the j-th charging pile in the time period corresponding to the i-th cycle, e0 is the total average fixed power loss, ε(i) is the random error value, and m is the total number of the multiple charging piles; The first calculation module is further used to establish, under an ideal condition where the pile error is regarded as 0, pile error estimation values ​​corresponding to the plurality of charging piles, and a functional relationship between the pile error estimation values ​​and the line loss estimation values ​​in the following manner: in, is the estimated value of the pile error, is the estimated value of the line loss.

8. The device according to claim 7, characterized in that The first determining module includes: A second acquisition unit, configured to acquire a first pile error estimation value that satisfies a first preset condition among the pile error estimation values ​​corresponding to the plurality of charging piles; A third calculation unit is used to calculate the means and variances corresponding to the plurality of first pile error estimation values ​​when there are a plurality of first pile error estimation values; A second determining unit, configured to determine a second pile error estimation value according to the mean and the variance; The third determining unit is used to determine the target line loss increment estimate value based on the second pile error estimate value and the functional relationship.

9. A non-volatile storage medium, characterized in that: The non-volatile storage medium stores a plurality of instructions, and the instructions are suitable for being loaded by a processor and executed by the line loss estimation method for a charging pile as described in any one of claims 1 to 6.

10. An electronic device, characterized in that: include: One or more processors and a memory, the memory being used to store one or more programs, wherein when the one or more programs are executed by the one or more processors, the one or more processors implement the line loss estimation method for a charging pile as described in any one of claims 1 to 6.

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